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Estimation of Crystal Orientation of Grains on Polycrystalline Silicon Substrate by Recurrent Neural Network
IEEJ Transactions on Electrical and Electronic Engineering ( IF 1.0 ) Pub Date : 2022-07-05 , DOI: 10.1002/tee.23676
Hikaru Kato 1 , Soichiro Kamibeppu 2 , Takuto Kojima 1 , Tetsuya Matsumoto 1 , Hiroaki Kudo 1 , Yoshinori Takeuchi 3 , Kentaro Kutsukake 4 , Noritaka Usami 2
Affiliation  

To analyze crystal defects in polycrystalline silicon substrates, it is necessary to measure the crystal orientation at high speed. In this paper, we propose a method for simultaneous and fast estimation of the crystal orientation of an entire substrate by measuring the reflected light from a single rotation of a light source. The effectiveness of the proposed method is verified by the orientation estimation experiments. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

中文翻译:

递归神经网络估计多晶硅衬底上晶粒的晶体取向

为了分析多晶硅衬底中的晶体缺陷,需要高速测量晶体取向。在本文中,我们提出了一种通过测量光源单次旋转的反射光来同时快速估计整个基板的晶体取向的方法。通过方向估计实验验证了所提方法的有效性。© 2022 日本电气工程师学会。由 Wiley Periodicals LLC 出版。
更新日期:2022-07-05
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